Nonparametric Statiscal Methods and Relate Topics

Friends and colleagues of Bhattacharya (emeritus, statistics, U. of California-Davis) present 22 papers on recent research, general nonparametric inference, aspects of linear or generalized linear models, time series analysis, and asymptotic theory. Specific topics include the propensity score and its role in causal inference, estimating density by sampling from stationary continuous time parameter associated processes, nonparametric models for non-Gaussian longitudinal data, a hybrid approach to parametric and nonparametric regression, a dynamic test for misspecification of a linear model, extreme dependence in multivariate time series, and convergence rates of an improved isotonic regression estimator. There is no index. Annotation c2012 Book News, Inc., Portland, OR (booknews.com)